Session 1B Snow Processes and Melt Detection through Remote Sensing, Modeling, and Data Assimilation

Monday, 7 January 2019: 8:30 AM-10:00 AM
North 126BC (Phoenix Convention Center - West and North Buildings)
Host: 33rd Conference on Hydrology
Cochairs:
Elias J. Deeb, Cold Regions Research and Engineering Lab, Remote Sensing and GIS, Hanover, NH; Carrie Vuyovich, Cold Regions Research and Engineering Lab, Remote Sensing and GIS, Hanover, NH and John B. Eylander, U.S. Army Corps of Engineers, Engineer Research and Development Center, Cold Regions Research and Engineering Lab, Hanover, NH

In snow-dominated basins across the globe, efficient water resource management requires accurate, timely estimates of both snow water equivalent (SWE) and snow melt onset. Melting snow provides a reliable water supply and can also produce wide-scale flooding hazards, particularly when combined with rainfall. An accurate estimate of snow volume, melt timing and the spatial distribution of both parameters is important for predicting runoff response for water resource and hydropower management as well as providing insight into important ecological and biogeochemical processes.  Remote sensing and modeling techniques provide methods for observing and detecting snow evolution, onset of snowmelt, spatial extent of melt processes, and vulnerability to extreme flood hazards that may result.  Both existing and novel remote sensing techniques have been developed to estimate snow evolution timing including the detection of liquid water in the snowpack.  Snow reconstruction and energy balance snow models have shown the ability to estimate snow properties, such as snow volume, liquid water content and melt. Observational, in-situ datasets that drive these models with meteorological inputs and modify the model through data assimilation techniques are critical in accurately portraying the natural phenomena of snow evolution. Reanalysis datasets have also proven valuable to forensically investigate large flooding events caused by snow melt. This session invites interdisciplinary research on existing and novel methods for remote sensing, modeling, and data assimilation of snow evolution, particularly snow melt timing and efforts linked to increased volume of discharge for water resource and hydropower management as well as resiliency and vulnerability to extreme flood events.

Papers:
8:30 AM
1B.1
Snow–Vegetation Interactions and Artifacts in Coordinated Remote Sensing and Ground Observation Studies
Christopher A. Hiemstra, Cold Regions Research and Engineering Lab, U.S. Army Corps of Engineers, Fort Wainwright, AK; and L. Brucker, H. P. Marshall, and K. Elder
8:45 AM
1B.2
9:00 AM
1B.3
CREST-SAFE Field Experiment: Comparison and Validation Remote Sensing Observations of Snow Surfaces
Tarendra Lakhankar, NOAA-CREST, New York, NY; and P. Romanov and R. Khanbilvardi
9:30 AM
1B.5
Satellite Detection of Snowmelt Events for Improving Spring Flood Forecasts in the Red River of the North Basin
Ronny Schroeder, Univ. of New Hampshire, Durham, NH; and S. Kraatz, J. M. Jacobs, B. A. Connelly, and M. M. DeWeese
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